Embedded Files
Test 1 on 02/06/2020; 4:30pm Portions: Lecture 1 to Lecture 5 slides; Also refer Textbook
Test 1 on 02/06/2020; 4:30pm Portions: Lecture 1 to Lecture 5 slides; Also refer Textbook
Download Test 1 Question Paper here at 4:20pm.
Upload signed and scanned answer book in pdf form here with filename: YourName4digitUSN.pdf
Test 2 on 12/06/2020; 4:30pm Portions: Lecture 6-7 Frequency Domain Processing,8-9 Color Image Processing slides; Also refer Textbook
Test 2 on 12/06/2020; 4:30pm Portions: Lecture 6-7 Frequency Domain Processing,8-9 Color Image Processing slides; Also refer Textbook
Download Test 2 Question Paper here at 4:20pm.
Upload signed and scanned answer book in pdf form here before 6:15pm with filename: YourName4digitUSN.pdf
Test 3 on 23/06/2020; 4:30pm Portions: Lecture 10-11 Morphological Operations,12-13 Wavelets, 14-15 Image Compression ; Also refer Textbook
Test 3 on 23/06/2020; 4:30pm Portions: Lecture 10-11 Morphological Operations,12-13 Wavelets, 14-15 Image Compression ; Also refer Textbook
Download Test 3 Question Paper here at 4:20pm.
Upload signed and scanned answer book in pdf form here before 6:00pm with filename: YourName4digitUSN.pdf
Event 4 download here; Deadline June 30, 2020 Submit here using Google Form
Event 2 Deadline May 10th 2020 Submit here using Form
Frequency Domain Filtering Program
Lecture 1: Image Fundamentals PPT
Lecture 2: Image Fundamentals-2 PPT
Lecture 4: Image Enhancement 2
Lecture 5: Image Sharpening/Edge detection
Lecture 6, 7: Processing in Frequency Domain
Lecture 8-9 Color Spaces and Color Image Processing
Lecture 10-11 Morphological Operations
Lecture 12-13 Wavelets and Multiresolution Analysis
Lecture 14-15 Image Compression
Elective 4:1:0 Course
Course Outcomes: After the end of the course student will be able to
understand image acquisition concepts using sensors and machines.
analyze algorithms for image processing using spatial domain operations.
analyze process image using frequency domain techniques.
apply morphological and segmentation operations.
implement image processing algorithms using open CV library.
Syllabus
Syllabus
UNIT 1
Digital Image Fundamentals: Elements of visual perception, Light and electromagnetic spectrum, image sensing and acquisition, Image sampling and quantization, Basic relationships between pixels.
Introduction to Open CV, Basics, installation, libraries
Image Enhancement in Spatial Domain: Basic gray level transformations, histogram processing, equalization, enhancement, image subtraction, averaging, smoothing and sharpening using spatial filters and their combination.
Image read write, enhancement in spatial domain using Open CV
12 hrs
UNIT 2
Image Enhancement in Frequency Domain: 2dimentional DFT, correspondence between filtering in spatial and frequency domain, smoothing and sharpening using Butterworth and Guassian Lowpass and highpass filters, Convolution, correlation, FFT and IFFT in 2d.
Image enhancement in frequency domain using Open CV 10 hrs
UNIT 3
Color image processing: Color models RGB, CMY, HSI, Color transformations, Smoothing and sharpening, Segmentation in HSI and RGB color space
Basic Morphological Algorithms: Dilation and erosion, Opening and closing, boundary extraction, region filling, extraction of connected components, thinning, thickening and pruning.
Color image segmentation and morphological operations using Open CV
12 hrs
UNIT 4
Image segmentation: Point, line and edge detection (Robert, Canny and Prewitt techniques). Character segmentation, circular object detection using Hough's transform. Segmentation using Open CV functions.
10 hrs
UNIT 5
Case studies: Character recognition, Braile recognition, Signature matching, face detection problems from recent journals 6 hrs
Books
Books
Rafael Gonzalez, Richard Woods, Digital Image Processing, 3rd Edition, 2017, Pearson India
Anil K. Jain, Fundamentals of Digital Image Processing, 2010 Economic Edition,Prentice Hall of India,
Gloria Bueno Garcia, Oscar Deniz Suarez, Learning Image Processing with OpenCV, Packt Publishing Limited, 2015.
MATLAB Files
Tutorial 1: Basic file format conversion
Tutorial 2: Logical ops and histogram
Tutorial 3: Spatial domain filtering
Tutorial 4.1: Frequency domain filtering
Tutorial 4.2 Edge Detection Demo
Tutorial 5: Color Image Processing
Tutorial 6: Iris Boundary Detection
CIE Breakup
3 Tests 20 marks each,
+2 Miniprojects 20 marks
Related Links:
Page updated
Google Sites
Report abuse